Analyte identification is difficult in complex biological samples which may contain numerous different analytes. For instance, metabolite identification is a bottleneck of most metabolomics studies. Common analysis techniques used with complex biological samples often include a separation step, such as chromatography, followed by a quantitative and/or qualitative detection step, such as mass spectrometry. Yet, in complex samples many of the analytes co-elute at the same retention time and/or appear in similar regions of the mass/charge (m/z) scale making determinations difficult. Additionally, the presence of noise signals, impurities associated with sample collection or extraction procedures, etc. and the presence of other non-biological related material can also interfere with the analysis.
The use of stable-isotope assisted methods, including labeling and internal standard approaches, can mitigate some of these difficulties. See Jong et al., “Addressing the current bottlenecks of metabolomics: Isotopic ratio outlier analysis, an isotopic-labeling technique for accurate biochemical profiling,” Bioanalysis, 2012 September, 4(18), 2303-2314; Stugg et al., “Isotopic ratio outlier analysis global metabolomics of Caenorhabditis elegans,” Anal. Chem. 2013, 85, 11858-11865; Zhou et al., “IsoMS: Automated processing of LC-MS data generated by a chemical isotope labeling metabolomics platform,” Anal. Chem. 2014. 86, 4675-4679; and Mahieu et al., “Credentialing features: A platform to benchmark and optimize untargeted metabolomics methods,” Anal. Chem. 2014, 86, 9583-9589, each of these references are incorporated by reference herein in their entirety. In simple situations, such as where the biological relevant analytes have been identified or are known, the characterization of their structure often relies only on accurate mass and isotopic pattern. In complex samples, the characterization is more challenging. These stable-isotope assisted methods used in conjunction with MS information or data dependent acquisition provide limited ability to overcome these challenges and provide robust structural elucidation. Additional techniques and methodology is needed for rapid and robust quantification and qualification of complex samples.